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06/01/2023
Unfair Utilities and First Steps Towards Improving Them
Many fairness criteria constrain the policy or choice of predictors. In ...
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03/31/2023
Simple Sorting Criteria Help Find the Causal Order in Additive Noise Models
Additive Noise Models (ANM) encode a popular functional assumption that ...
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03/11/2022
Identifying Causal Effects using Instrumental Time Series: Nuisance IV and Correcting for the Past
Instrumental variable (IV) regression relies on instruments to infer cau...
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02/12/2022
Learning by Doing: Controlling a Dynamical System using Causality, Control, and Reinforcement Learning
Questions in causality, control, and reinforcement learning go beyond th...
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03/29/2021
Compositional Abstraction Error and a Category of Causal Models
Interventional causal models describe joint distributions over some vari...
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02/26/2021
Beware of the Simulated DAG! Varsortability in Additive Noise Models
Additive noise models are a class of causal models in which each variabl...
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02/21/2020
Causal structure learning from time series: Large regression coefficients may predict causal links better in practice than small p-values
In this article, we describe the algorithms for causal structure learnin...
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02/14/2020
Distributional robustness as a guiding principle for causality in cognitive neuroscience
While probabilistic models describe the dependence structure between obs...
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06/04/2018
groupICA: Independent component analysis for grouped data
We introduce groupICA, a novel independent component analysis (ICA) algo...
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07/04/2017
Causal Consistency of Structural Equation Models
Complex systems can be modelled at various levels of detail. Ideally, ca...
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05/23/2016
A note on the expected minimum error probability in equientropic channels
While the channel capacity reflects a theoretical upper bound on the ach...
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05/02/2016
Recovery of non-linear cause-effect relationships from linearly mixed neuroimaging data
Causal inference concerns the identification of cause-effect relationshi...
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03/10/2016
Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic Differentiation
Optimization on manifolds is a class of methods for optimization of an o...
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12/15/2015
Causal and anti-causal learning in pattern recognition for neuroimaging
Pattern recognition in neuroimaging distinguishes between two types of m...
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12/14/2015
Decoding index finger position from EEG using random forests
While invasively recorded brain activity is known to provide detailed in...
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12/03/2015
MERLiN: Mixture Effect Recovery in Linear Networks
Causal inference concerns the identification of cause-effect relationshi...
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11/15/2015